The relationship between serum ferritin level and clinical outcomes in sepsis based on a large public database

This study aimed to investigate the relationship between serum ferritin level and prognosis in sepsis. It also explored the potential prognostic value of serum ferritin for predicting outcomes in sepsis based on a large public database. Sepsis patients in MIMIC-IV database were included. Different models including crude model (adjusted for none), model I (adjusted for age and gender) and model II (adjusted for all potential confounders) were performed. Smooth fitting curves were constructed for exploring the relationships between serum ferritin and mortalities of 28-day, 90-day, 180-day and 1-year. Receiver operator characteristic (ROC) curve analysis was utilized for assessing the predictive value of serum ferritin. 1947 sepsis patients were included. The mortalities of 28-day, 90-day, 180-day and 1-year were 20.18% (n = 393), 28.35% (n = 552), 30.30% (n = 590) and 31.54% (n = 614), respectively. In Model II (adjusted for all potential confounders), for every 1000 ng/ml increment in serum ferritin, the values of OR in mortalities of in 28-day, 90-day, 180-day and 1-year were 1.13 (95% CI 1.07–1.19, P < 0.0001), 1.15 (95% CI 1.09–1.21, P < 0.0001), 1.16 (95% CI 1.10–1.22, P < 0.0001) and 1.17 (95% CI 1.10–1.23, P < 0.0001), respectively. The relationships between serum ferritin level and outcomes were non-linear. The areas under the ROC curve (AUC) of ferritin for predicting mortalities of 28-day, 90-day, 180-day and 1-year were 0.597 (95% CI 0.563–0.629), 0.593 (95% CI 0.564–0.621), 0.595 (95% CI 0.567–0.623) and 0.592 (95% CI 0.564–0.620), respectively. The non-linear relationships between serum ferritin and clinical outcomes in sepsis were found. Serum ferritin had a predictive value for short-term and long-term outcomes in sepsis.

Study design. We enrolled the septic patients from MIMIC-IV for data analysis. The definition of Sepsis 3.0 was applied for confirming the sepsis, which indicated that sepsis was diagnosed with infection and sequential organ failure assessment (SOFA) score ≥ 2 points 18 . Patients who met the criteria as follow were excluded: (1) missing data of serum ferritin within 24 h after admission; (2) missing data > 5% individual variables; (3) < 18 years old.

Information and variables.
Variables were extracted within 24 h after admission and only the first record of each variable was utilized.
Statistical analysis. EmpowerStats (http:// www. empow ersta ts. com) and the software packages R (http:// www.R-proje ct. org) were applied for statistical analysis. Statistically significant was considered when the P value was less than 0.05.
The septic patients were divided into four group (Q1 (≤ 244 ng/ml, n = 486), Q2 (245-542 ng/ml, n = 485), Q3 (543-1124 ng/ml, n = 488), Q4 (≥ 1125 ng/ml, n = 488)) based on the quartiles of serum ferritin level (Table 1). Different variables were expressed as follow: medians for continuous variables, and percentages or frequencies for categories variables. Chi-squared test and Mann-Whitney U-test were applied for variables analysis between four groups. Univariate analysis for clinical outcomes including 28-day mortality, 90-day mortality, 180-day mortality and 1-year mortality was performed. Associations between serum ferritin and outcomes were investigated in three models: crude model (adjusted for none), model I (adjusted for age and gender) and model II (adjusted for all potential confounders). Covariates were included as potential confounders in the final models if they changed the estimates of ferritin on 1-year mortality in sepsis by more than 10% or were significantly associated with clinical outcomes in sepsis 19,20 . The calculating steps were showed in Supplementary materials. The following covariates were selected a priori on the basis of established associations and/or plausible biological relations and tested: age; ALT; AG; total calcium; creatinine; hematocrit; hemoglobin; PLT; PT; TT; RDW; RBC; urea nitrogen; renal disease; APAHCEII; SOFA. In addition, gender, as a common confounder in many previous studies 21,22 , was also added to be adjusted in the final models.
In addition, two models including model A (linear model) and model B (two-segment nonlinear model) were utilized for comparison and the better one was selected based on the P value. If < 0.05, the nonlinear model was the better and the turning point of serum ferritin was calculated. The smooth fitting curves were performed for indicating the relationships between serum ferritin level and outcomes. Kaplan-Meier analysis for survival probability in four groups (Q1-Q4) was constructed. Subgroup analysis was done for investigating the stability of the results. The receiver-operator characteristic (ROC) analysis of serum ferritin for predicting outcomes were performed. The different performances of ferritin, SOFA score and APAHCEII score including specificity, sensitivity and cut-off value were analyzed. Ethical approval. This study was conducted in accordance with Declaration of Helsinki 2002. MIMIC-IV was an anonymized public database. To apply for access to the database, we passed the Protecting Human Research Participants exam (No.32900964). The project was approved by the institutional review boards of the Massachusetts Institute of Technology (MIT) and Beth Israel Deaconess Medical Center (BIDMC) and was given a waiver of informed consent.
The median days of LOS in ICU and hospital were 6.72 and 17.28, respectively. The mortalities of in 28-day, 90-day, 180-day and 1-year Q4 groups were the highest compared to Q1-Q3 groups, which were 29.51%, 39.14%, 41.39% and 42.42%, respectively. Table 2. Univariate analysis for different outcomes in sepsis patients. ALT, alanine aminotransferase; AST, aspartate aminotransferase; CAD, coronary artery disease; SBP, systolic blood pressure; DBP, diastolic blood pressure; HR, heart rate; RR, respiratory rate; WBC, white blood cells; PLT, platelet; RDW, red blood cell distribution width; RBC, red blood cells; PT, prothrombin time; TT, thrombin time; AG, anion gap; APACHE, acute physiology and chronic health evaluation; SOFA, sequential organ failure assessment; OR, odds ratio; CI, confidential interval.   www.nature.com/scientificreports/ A non-linear relationship between serum ferritin and outcomes. In Table 4, we compared two models including the linear model (model A) and two-segment non-linear model (model B) in all clinical outcomes and found that all the P values for the log-likelihood ratio test were less than 0.05, which indicated the non-linear model was better for expressing the association between serum ferritin and clinical outcomes. In Fig. 1, smooth fitting curves were constructed, which demonstrated the non-linear relationships between serum ferritin level and mortalities of 28-day (A), 90-day (B), 180-day (C) and 1-year (D). The turning points of serum ferritin in the four clinical outcomes were 2340 ng/ml, 2250 ng/ml, 2280 ng/ml and 2300 ng/ml, respectively.

Association between serum ferritin and outcomes in different models.
Kaplan-Meier analysis for survival probability. Figure 2 illuminated Kaplan-Meier analysis for survival probability in four groups (Q1-Q4). In Q4 group, the lowest survival probabilities in 28-day (A), 90-day (B), 180-day(C) and 1-year (D) were found (all P < 0.001). Prognostic value of ferritin in predicting clinical outcomes. In Table 5

Discussion
In the present study, the non-linear relationships between serum ferritin and clinical outcomes in sepsis were found. For every 1000 ng/ml increment in serum ferritin, the risks in mortalities of in 28-day, 90-day, 180-day and 1-year increased by 13%, 15%, 16% and 17%, respectively. In addition, serum ferritin had a predictive value for outcomes in sepsis. Ferritin, as a significant protein in iron metabolism, was involved both in the iron homeostasis and inflammatory process [23][24][25] . The potential prognostic and diagnostic values of serum ferritin level have been proved in various disorders [25][26][27] . In hemophgocytosis, a serum ferritin > 2000 ug/l for predicting mortality had a specificity of 76% and a sensitivity of 71% 28 . In hospitalized patients, ferritin levels greater than 2000 ng/ml were identified to be significantly associated with severe diseases 29 . In metabolic syndrome, the serum ferritin levels were found to be positively related with the levels of insulin resistance, cholesterol, and triglyceride 30 . One recent study with hemorrhagic fever with renal syndrome in China revealed that the value of serum ferritin for predicting mortality was comparatively good compared with procalcitonin and C-reactive protein 31 . For all-cause mortality risk within five-year in hemodialysis patients, serum ferritin > 1500 ng/ml was an early indicator 32 .
In critical ill and sepsis, accumulating evidences also clarified the close relationship between serum ferritin and clinical outcomes. In children with sepsis and septic shock, a ferritin > 500 ng/ml increased the relative risk of mortality with a 2.2 folds 33 . For predicting death in multiple organ dysfunction due to sepsis, 1994.3 ng/ml might be a cut-off value in serum ferritin 34 . Ferritin > 4420 ng/ml was described to be diagnostic of macrophage activation-like syndrome and predictive of short (10-day) and 28-day mortality in sepsis 35 . Current evidence suggested the biomarker of serum ferritin was good for immunotyping and providing immunomodulatory treatment in sepsis with encouraging results 36 . Based on the results from one large research in critical ill patients, the AUCs for ferritin in predicting in-hospital mortality and organ failure were 0.655 and 0.646, respectively. In sepsis, the AUCs for ferritin in predicting in-hospital mortality and organ failure were 0.628 and 0.608, respectively, which the cut-off values were 411 ng/ml and 581 ng/ml, respectively 37 , which were partly similar with our results.
The potential mechanisms why elevated serum ferritin levels were correlated with poorer outcomes in sepsis could be explained as follow: (1) The inflammation due to sepsis usually produces the endotoxin, which upregulates the ferritin coding gene and leads to increased levels of serum ferritin 38 ; (2) Ferroptosis, as a way of cell death, might be mediated by different levels of serum ferritin, resulting in cellular injury and organ dysfunction 39 ; (3) Inflammatory cytokines are able to upregulate the ferritin production, which in turn strengthens the release of proinflammatory and anti-inflammatory factors, leading to more severe inflammatory response and poor prognosis 40,41 .
The strength of our study was that we investigated the relationships between serum ferritin and clinical outcomes with short-term and long-term in sepsis and also explored the predictive values of serum ferritin. We found that serum ferritin was closely associated not only with short-term outcomes but also with 1-year mortality in sepsis patients. Moreover, serum ferritin also had a comparatively good value for predicting the outcomes in sepsis patients. It might help physicians to early differentiating the patients with higher risk of adverse outcomes. Table 5. Predictive performances of ferritin and scoring systems in clinical outcomes. AUC, area under the curve; CI, confidential interval; SOFA, sequential organ failure assessment; APACHE, acute physiology and chronic health evaluation; OR, odds ratio; CI, confidential interval. www.nature.com/scientificreports/ www.nature.com/scientificreports/ Anyway, some limitations in the research were not avoided. First, due to the lack of some data, some other factors of iron metabolism including transferrin, free iron level, and ferritin saturation were not included. Second, due to our exclusion criteria, the proportion of excluded subjects with missing variables might cause bias in the relationships. Due to the lack of serum ferritin, a number of sepsis patients were excluded. Third, it was a retrospective study based on public database and the limitations of applicability for our results should be considered. In the study, we only used the U.S public database and didn't validate our results in other cohorts. Further study with large samples in multiple centers and different regions should be done for validating our results.

Conclusion
In the present study, the non-linear relationships between serum ferritin and clinical outcomes in sepsis were found. In addition, serum ferritin had a predictive value for outcomes in sepsis.